Structural changes occurring in the crude oil market have stimulated the emergence of hypotheses suggesting that the relationship between prices of this raw material and the US dollar exchange rate can gradually become similar to that observed between oil prices and exchange rates of the currencies of the countries whose revenues from the export of this resource are a significant part of their current account balance. The purpose of this study was to determine and evaluate the time-varying dependence between oil prices and the exchange rate of the US dollar in the context of the same relationship for the Chinese, European, Japanese, Saudi, and Russian currencies. The results of our analyses implicate that a negative correlation between the variables in question grows stronger in time periods preceding global shocks and during thereof. The dominance of the USD in the crude oil market is reflected in similar characteristics of the correlations of the currencies of other countries, such a... [more]

The global maximum power point tracking of a PV array under partial shading represents a global optimization problem. Conventional maximum power point tracking algorithms fail to track the global maximum power point, and global optimization algorithms do not provide global maximum power point in real-time mode due to a slow convergence process. This paper presents an intelligent reconfigurable photovoltaic system on the basis of a modified fuzzy neural net that includes a convolutional block, recurrent networks, and fuzzy units. We tune the modified fuzzy neural net based on modified multi-dimension particle swarm optimization. Based on the processing of the sensors’ signals and the photovoltaic array’s image, the tuned modified fuzzy neural net generates an electrical interconnection matrix of a photovoltaic total-cross-tied array, which reaches the global maximum power point under non-homogeneous insolation. Thus, the intelligent reconfigurable photovoltaic system represents an effec... [more]

Transition to turbulence and changes in the fluid flow structure are subjects of continuous analysis and research, especially for unique fields of research such as the thermo-magnetic convection of weakly magnetic fluids. Therefore, an experimental and numerical research of the influence of an external magnetic field on a natural convection’s fluid flow was conducted in the presented research. The experimental part was performed for an enclosure with a 0.5 aspect ratio, which was filled with a paramagnetic fluid and placed in a superconducting magnet in a position granting the enhancement of the flow. The process was recorded as temperature signals from the thermocouples placed in the analyzed fluid. The numerical research enabled an investigation based not only on temperature, but velocities as well. Experimental and numerical data were analyzed with the application of extended fast Fourier transform and wavelet analysis. The obtained results allowed the determination of changes in th... [more]

This paper presents a detailed analysis of 1200 V Silicon Carbide (SiC) power MOSFET exhibiting different short-circuit failure mechanisms and improvement in reliability by VDS and VGS depolarization. The device robustness has undergone an incremental pulse under different density decreasing; either drain-source voltage or gate-driver voltage. Unlike silicon device, the SiC MOSFET failure mechanism firstly displays specific gradual gate-cracks mechanism and progressive gate-damage accumulations greater than 4 µs/9 J·cm−2. Secondly, a classical drain-source thermal runaway appears, as for silicon devices, in a time greater than 9 µs. Correlations with short-circuit energy measurements and temperature simulations are investigated. It is shown that the first mechanism is an incremental soft gate-failure-mode which can be easily used to detect and protect the device by a direct feedback on the gate-driver. Furthermore, it is highlighted that this new mechanism can be sufficiently consolida... [more]

In this study, a steady state model for burning of coal mine methane in a Reverse Flow Burner (RFB) with full kinetics was developed by analogy of a steady counter-flow reactor, and the developed model was used for quick prediction of the lean combustibility limit (LCL). The model was successfully validated with experimental and numerical results, and it was shown that the developed model has excellent accuracy and computational efficiency. Good agreement between the predicted temperature, LCL, and the experiments was observed. The LCL of the equivalence ratio of 0.022 for methane/air mixture was obtained by the developed model. The model was then used to evaluate LCL for the RFB, focusing on the effect of heat loss and burner length on LCL. This indicated that the computational time using the developed model can be reduced by a factor of 1560 compared to the complete transient model.

This paper presents the integration of advanced machine learning techniques in the medium voltage distributed monitoring system QuEEN. This system is aimed to monitor voltage dips in the Italian distribution network mainly for survey and research purposes. For each recorded event it is able to automatically evaluate its residual voltage and duration from the corresponding voltage rms values and provide its “validity” (invalidating any false events caused by voltage transformers saturation) and its “origin”(upstream or downstream from the measurement point) by proper procedures and algorithms (current techniques). On the other hand, in the last years new solutions have been proposed by RSE to improve the assessment of the validity and origin of the event: the DELFI classifier (DEep Learning for False voltage dips Identification) and the FExWaveS + SVM classifier (Features Extraction from Waveform Segmentation + Support Vector Machine classifier). These advanced functionalities have been... [more]

This paper newly proposes an interactive multiple model (IMM) algorithm to adaptively track distorted AC voltage with the grid frequency fluctuation. The usual tracking methods are Kalman filter (KF) algorithm with a fixed frequency and KF algorithm with frequency identifier. The KF algorithm with a fixed frequency has a larger covariance parameter to guarantee the tracking robustness. However, it has a large tracking error. The KF algorithm with frequency identifier overly depends on the accuracy and stability of frequency identifier. The advantage of the proposed method is that it is decoupled from frequency detection and does not depend on frequency detection accuracy. First, the orthogonal vector dynamic (OVD) tracking model of the sine wave is established. Then, a model set covering the grid frequency fluctuation range is formed, and a new OVD-IMM tracking algorithm is proposed in combination with IMM algorithm. In the end, the effectiveness and accuracy of the proposed OVD-IMM al... [more]

Wind energy has been recognized as the most promising and economical renewable energy source, attracting increasing attention in recent years. However, considering the variability and uncertainty of wind energy, accurate forecasting is crucial to propel high levels of wind energy penetration within electricity markets. In this paper, a comparative framework is proposed where a suite of long short-term memory (LSTM) recurrent neural networks (RNN) models, inclusive of standard, bidirectional, stacked, convolutional, and autoencoder architectures, are implemented to address the existing gaps and limitations of reported wind power forecasting methodologies. These integrated networks are implemented through an iterative process of varying hyperparameters to better assess their effect, and the overall performance of each architecture, when tackling one-hour to three-hours ahead wind power forecasting. The corresponding validation is carried out through hourly wind power data from the Spanis... [more]

Solar irradiance models contribute to mitigating the lack of measurement data at a ground station. Conventionally, the models relied on physical calculations or empirical correlations. Recently, machine learning as a sophisticated statistical method has gained popularity due to its accuracy and potential. While some studies compared machine learning models with other models, a study has not yet been performed that compares them side-by-side to assess their performance using the same datasets in different locations. Therefore, this study aims to evaluate the accuracy of three representative models for estimating solar irradiance using atmospheric variables measurement and cloud amount derived from satellite images as the input parameters. Based on its applicability and performance, this study selected the fast all-sky radiation model for solar applications (FARMS) derived from the radiative transfer approach, the Hammer model that simplified atmospheric correlation, and the long short-t... [more]

This article presents the methodology, description, and results of experimental studies aimed at determining the impact of the copper concentration in a carbon−metal composite contact strip on the maximum temperature of the copper contact wire during a contact event when used for operation in the railway industry in Europe. Based on these tests, we determined the minimum percentage of copper that is required for the composite to meet the normative requirements for current loads. In addition to experimental research, a 3D FEM numerical model was also developed in which the contact strip and contact wire geometry were mapped, along with imposed loads resulting from the test for current loads mentioned above. Fifteen simulation variants were carried out for the established model, where the value of the thermal conductivity coefficient and the specific heat coefficient were varied. On this basis, we analyzed the sensitivity of thermal coefficients to the contact wire temperature and determ... [more]

The vision of the smart city is inextricably linked with the concepts of intelligent transport, sustainable mobility and managerial decision making. Cities of the future not only entail the use of new technology, but also increasingly the interpenetration of technological and social aspects, with the simultaneous involvement of urban space users in the creation of such technologies. This provides an opportunity to introduce desired changes and create a more balanced space with a higher quality of life and improved energy efficiency. The article discusses the concepts of sustainable development and sustainable mobility with a particular emphasis on issues related to the smart city. The authors reviewed the various smart city solutions that have been implemented in the field of urban transport in Cracow, whose authorities have taken steps over the last few years to make the city smarter and more modern. The aim of the research was to assess the contribution made by smart city solutions t... [more]

This editorial document provides the main motivations and a brief description of each paper published in the “Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation” Special Issue. This Special Issue aims to present several innovative solutions on planning and operation of distribution power networks under smart grid paradigm where prosumers, electric vehicles, and other typical loads are usually connected. Some of those solutions and computational applications were covered in this Special Issue, namely probabilistic power flow, voltage and power factor control, agent-based simulation, digital twin, resilient energy scheduling, and uncertainty modeling are among the contributions. The published works are very timely and are of great interest, which will certainly drive the impact of future researchers in the near term concerning the field of this Special Issue.

Fuel starvation is a major cause of anode corrosion in low temperature polymer electrolyte fuel cells. The fuel cell start-up is a critical step, as hydrogen may not yet be evenly distributed in the active area, leading to local starvation. The present work investigates the hydrogen distribution and risk for starvation during start-up and after nitrogen purge by extending an existing computational fluid dynamic model to capture transient behavior. The results of the numerical model are compared with detailed experimental analysis on a 25 cm2 triple serpentine flow field with good agreement in all aspects and a required time step size of 1 s. This is two to three orders of magnitude larger than the time steps used by other works, resulting in reasonably quick calculation times (e.g., 3 min calculation time for 1 s of experimental testing time using a 2 million element mesh).

Forecasting consumption in isolated areas represents a challenging problem typically resolved using deep learning or huge mathematical models with various dimensions. Those models require expertise in metering and algorithms and the equipment needs to be frequently maintained. In the context of the MAESHA H2020 project, most of the consumers and producers are isolated. Forecasting becomes more difficult due to the lack of external data and the significant impact of human behaviors on those small systems. The proposed approach is based on data sequencing, sequential mining, and pattern mining to infer the results into a Hidden Markov Model. It only needs the consumption and production curve as a time series and adapts itself to provide the forecast. Our method gives a better forecast than other prediction machines and deep-learning methods used in literature review.

Inference is investigated for a multicomponent stress-strength reliability (MSR) under Type-II censoring when the latent failure times follow two-parameter Rayleigh distribution. With a context that the lifetimes of the strength and stress variables have common location parameters, maximum likelihood estimator of MSR along with the existence and uniqueness is established. The associated approximate confidence interval is provided via the asymptotic distribution theory and delta method. Meanwhile, alternative generalized pivotal quantities-based point and confidence interval estimators are also constructed for MSR. More generally, when the lifetimes of strength and stress variables follow Rayleigh distributions with unequal location parameters, likelihood and generalized pivotal-based estimators are provided for MSR as well. In addition, to compare the equivalence of different strength and stress parameters, a likelihood ratio test is provided. Finally, simulation studies and a real dat... [more]

Private vehicle travel is the most basic mode of transportation, so that an effective way to control the real-world fuel consumption rate of light-duty vehicles plays a vital role in promoting sustainable economic growth as well as achieving a green low-carbon society. Therefore, the factors impacting individual carbon emissions must be elucidated. This study builds five different models to estimate the real-world fuel consumption rate of light-duty vehicles in China. The results reveal that the light gradient boosting machine (LightGBM) model performs better than the linear regression, naïve Bayes regression, neural network regression, and decision tree regression models, with a mean absolute error of 0.911 L/100 km, a mean absolute percentage error of 10.4%, a mean square error of 1.536, and an R-squared (R2) value of 0.642. This study also assesses a large pool of potential factors affecting real-world fuel consumption, from which the three most important factors are extracted, name... [more]

In time attack races, aerodynamics plays a vital role in achieving short track times. These races are characterized by frequent braking and acceleration supported by aerodynamic downforce. Usually, typical cars are modified for these races by amateurs. Adjusting the aerodynamic solutions to work with bodies developed for other flow conditions is difficult. This paper presents the results of a numerical analysis of the effects of installing a straight wing in front of or above the body on the modified vehicle system’s aerodynamic characteristics, particularly on the front wheels’ aerodynamic downforce values. The paper presents the methodology and results of calculations of the aerodynamic characteristics of a car with an additional wing placed in various positions in relation to the body. The numerical results are presented (Cd, Cl, Cm, Clf, Clr), as well as exemplary pressure distributions, pathlines, and visualizations of vortex structures. Strong interactions between the wing operat... [more]

Power demand-side management has been identified as one of the possible elements towards a more flexible power system in case of increased capacities of variable renewable energy sources—solar and wind energy. The market coordinators or aggregators are introduced to adjust the electricity consumption by following the market situation. However, the role of aggregators is mainly analysed from the economic perspective, and the demand side management is performed to maximise the utilisation of low price power during off-peak hours. However, this research focuses on analysing the introduction of aggregators as a future player to increase the total share of renewable power and decrease the surplus solar and wind electricity occurrence. An in-depth system dynamics model has been developed to analyse the hourly power production and power consumption rates at the national level for the Latvia case study. The results show that introducing aggregators and load shifting based on standard peak shav... [more]

The paper presents an analysis of the hygrothermal performance of an inverted flat roof with a CLT (cross-laminated timber) structure in a building that meets the requirements of Passive House Standard (PHS) with regards to the potential risk of moisture. The calculations were made in the WUFI®Plus and WUFI®Bio software. The following variants were taken into account: three structure configurations, three different external climates and different scenarios of microclimate control and air change rate. The results of the calculations show that, especially in cooler climates, there is an actual moisture risk in the structure despite the excellent thermal insulation. The structure of the inverted flat roof, due to the use of a tight membrane on the outer side, allows for the partition to discharge the excess moisture only to the inside of the building. Ensuring the comfort of users may require periodic humidification of internal air, which translates directly into an increase in moisture c... [more]

Analyses and comparisons of generic models and a novel modeling method of line-commutated converter (LCC)-based high voltage direct current (HVDC) systems are presented for the power system simulator for engineering (PSS/E) simulation tool. The main purposes are to describe the dynamics of the DC voltage and current of HVDC system and to improve estimation of the maximum values using the generic and proposed HVDC models when AC line-to-ground faults are occurred. For the generic HVDC models, the characteristics and limitations as well as parameter investigations are conducted. Three modules are also are developed for the proposed HVDC model, which are composed of (a) AC/DC conversion; (b) controller selection; and (c) DC line model. Case studies were conducted considering the real-operated HVDC system in Korea under the PSS/E and power systems computer aided design (PSCAD) simulation environments. The simulation results were compared with measured data from the real-operated HVDC syste... [more]

The temperature properties of real-type direct-current gas-insulated transmission lines (DC-GIL) with a basin-type spacer were investigated by the finite element method in this paper. A horizontally installed model was established and the temperature distribution was obtained with a 3D model. The specific heat capacity and thermal conductivity of the spacer were measured and applied in the simulation. The results show that the temperature of the convex surface was slightly higher than that of the concave surface. With an increase in the SF6 pressure, the temperature of the spacer decreased, which can be attributed to the improvement of convection due to increases in the heat capacity per unit volume. With an increase in the ambient temperature, the temperature of the spacer increased linearly. The temperature difference between the inner and outer parts of the spacer increased with increases in the load current. Besides, an obvious increase in the surface electric field strength appear... [more]

The e-commerce industry has been developing extremely dynamically for many years. This development was intensified during the COVID-19 pandemic. According to the research conducted by the authors of this paper, in Poland, during the pandemic, the number of delivered parcels increased 20−100%, depending on the courier company. The research of the authors of this article focused on the energy efficiency of the last mile, which is very important for the efficiency of the entire delivery process to customers. As the authors calculated, the last mile can consume over 70% of energy of the whole distribution channel. The article presents the results of research concerning the energy efficiency of deliveries performed by couriers and express companies in Poland. Two models of distribution used Poland have been compared—direct deliveries to final customers, and deliveries to parcel lockers. The research methods are interviews with the managers and couriers, analysis of the literature, and the s... [more]

The removal of solids is the most important step when treating rainwater. The article evaluates two designs of sedimentation tanks that can be used for the continuous separation of fine particles from water: OS—standard sedimentation tanks, and OW—swirl sedimentation tanks. The tanks were studied by conducting computational fluid dynamics (CFD) modeling and particle image velocimetry (PIV) experiments. The settling process in sedimentation tank was carried out at varying operating flow rates. A tank with a modified structure was used for the tests, where water was supplied by a nozzle placed at an angle. This solution made it possible to obtain a rotational flow that transported the suspended particles towards its wall, where downward axial velocity resulted in the settling of particles. Based on the research, it was observed that the flow patterns showed inward flow at the bottom of the tank and an upward flow and the lifting of the settled particles near the hatch at the bottom. The... [more]

In this work, a data-driven methodology for modeling combustion kinetics, Learned Intelligent Tabulation (LIT), is presented. LIT aims to accelerate the tabulation of combustion mechanisms via machine learning algorithms such as Deep Neural Networks (DNNs). The high-dimensional composition space is sampled from high-fidelity simulations covering a wide range of initial conditions to train these DNNs. The input data are clustered into subspaces, while each subspace is trained with a DNN regression model targeted to a particular part of the high-dimensional composition space. This localized approach has proven to be more tractable than having a global ANN regression model, which fails to generalize across various composition spaces. The clustering is performed using an unsupervised method, Self-Organizing Map (SOM), which automatically subdivides the space. A dense network comprised of fully connected layers is considered for the regression model, while the network hyper parameters are o... [more]

Minimum miscible pressure (MMP) is an essential design parameter of gas flooding for enhanced oil recovery (EOR) applications. Researchers have developed a number of methods for MMP computations, including the analytical methods, the slim-tube simulation method, and the multiple-mixing-cell (MMC) method. Among these methods, the MMC method is widely accepted for its simplicity, robustness, and moderate computational cost An important version of the MMC method is the Jaubert et al. method which has a much lower computational cost than the slim-tube simulation method. However, the original Jaubert et al. method suffers several drawbacks. One notable drawback is that it cannot be applied to the scenario where the oil-gas MMP is lower than the saturation pressure of the crude oil. In this work, we present a modified MMC method that is more versatile and robust than the original version. Our method can handle the scenario where the oil-gas MMP is lower than the saturation pressure of the cr... [more]